DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Phoenix vs. Graph Engine vs. Heroic vs. Teradata Aster vs. Tkrzw

System Properties Comparison Apache Phoenix vs. Graph Engine vs. Heroic vs. Teradata Aster vs. Tkrzw

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonHeroic  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchPlatform for big data analytics on multistructured data sources and typesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSGraph DBMS
Key-value store
Time Series DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitephoenix.apache.orgwww.graphengine.iogithub.com/­spotify/­heroicdbmx.net/­tkrzw
Technical documentationphoenix.apache.orgwww.graphengine.io/­docs/­manualspotify.github.io/­heroic
DeveloperApache Software FoundationMicrosoftSpotifyTeradataMikio Hirabayashi
Initial release20142010201420052020
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20190.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoMIT LicenseOpen Source infoApache 2.0commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava.NET and CJavaC++
Server operating systemsLinux
Unix
Windows
.NETLinuxLinux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononoyes infoin Aster File Storeno
Secondary indexesyesyes infovia Elasticsearchyes
SQL infoSupport of SQLyesnonoyesno
APIs and other access methodsJDBCRESTful HTTP APIHQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C#
C++
F#
Visual Basic
C
C#
C++
Java
Python
R
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsyesnoR packagesno
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioningShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnonoyes infousing specific database classes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyfine grained access rights according to SQL-standardno

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache PhoenixGraph Engine infoformer name: TrinityHeroicTeradata AsterTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021,  Krishna Maheshwari (sponsor) 

show all

Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

Amazon EMR 4.7.0 – Apache Tez & Phoenix, Updates to Existing Apps | Amazon Web Services
2 June 2016, AWS Blog

Suspects in violent Payson casino robbery were employees, FBI says
7 August 2018, KTAR.com

provided by Google News

Trinity
2 June 2023, Microsoft

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

The graph analytics landscape 2019 - DataScienceCentral.com
27 February 2019, Data Science Central

How Google and Microsoft taught search to "understand" the Web
6 June 2012, Ars Technica

provided by Google News

Northwestern Analytics Partners with Teradata Aster to Host Hackathon
23 May 2014, Northwestern Engineering

Teradata Aster gets graph database, HDFS-compatible file store
8 October 2013, ZDNet

Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business
22 September 2011, PR Newswire

Teradata's Aster shows how the flowers of fraud bloom
23 April 2015, The Register

Case study: Siemens reduces train failures with Teradata Aster
12 September 2016, RCR Wireless News

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Present your product here